CV Analyzer reads a candidate’s CV and gives you a score, structured rationale, strengths, gaps, and interview questions in about a minute. The recruiter still makes the call — every call.
No signup · No card · CV text processed and discarded
CV Analyzer slots into your existing screening flow. It does not replace your ATS, your judgment, or your hiring decisions.
Paste the CV text into the browser. No file upload, no PDF parsing, no integration to set up.
You get a score, rationale, strengths, gaps, and 3-5 interview questions in about a minute.
You read the analysis, apply your own judgment, cross-check against the role you actually need to fill.
You decide who moves forward. The system does not auto-shortlist, auto-reject, or send any candidate communication.
We are deliberate about what this tool does and does not do. Recruiters and hiring managers stay accountable for the outcome.
Recruitment touches personal data. We try to keep our exposure — and yours — small.
Consent-based processing. CV text is processed only when a recruiter or candidate explicitly submits it. There is no scraping, no enrichment from third-party data brokers.
Process and discard. CV text is sent to the model, used to generate the analysis, and discarded after the response. We do not retain CV bodies and we do not train on your inputs.
EU-hosted account data. When you create an account (optional for basic use), account data lives in Supabase EU data centres. Payments go through Stripe.
Redacted logging. Operational logs use redacted metadata. We log enough to debug and rate-limit, not enough to reconstruct a CV.
Data subject requests. Standard GDPR rights apply (access, correction, erasure, portability, objection). Email the addresses below.
This is the kind of output CV Analyzer returns — score, rationale, strengths, gaps, and a sample interview question. The example below is illustrative, generated for this page.
Solid match on the core stack. Clear ownership signals on two recent roles; some gaps around system-design depth and on-call experience that are worth probing in interview.
Output is AI-generated and advisory. The recruiter decides what to do with it.
Try this on a real CV at /cv/try
The kinds of problems CV Analyzer is built to help with.
A first-pass structured read in about a minute. Useful when you have 40 CVs in the queue and 90 minutes between calls.
Same prompt, same structure, same fields per CV — so two candidates evaluated an hour apart get rationale you can actually compare side by side.
The score and gaps section help you decide which CVs deserve the deeper read — not which candidates get rejected. You stay in the loop on every advance.
Standalone in the browser. No ATS plugin to install, no IT ticket to file. Paste, read, copy what is useful into your existing pipeline.
The free trial takes about a minute. If you want a higher-volume setup or something tailored to your team — recruiter workflows, ATS exports, custom rubrics — talk to us.
No. CV Analyzer produces a score, structured rationale, strengths, gaps, and suggested interview questions. A human recruiter reads that, applies their own judgment, and decides who to advance. We do not auto-shortlist or auto-reject candidates.
CV Analyzer is free to try at /cv/try with no signup and no card. There is a per-IP daily rate limit on the free tier. Paid usage on a credit-pack basis is in development for higher-volume recruiting workflows; pricing is not finalised yet.
CV text is processed in real time to generate the analysis and discarded after the response. We do not store CVs or train on your inputs. Account data (when you create one) lives in EU data centres via Supabase. Full details in our Privacy Policy.
Not yet. Today CV Analyzer is a standalone tool — paste a CV in the browser, read the analysis, copy what you need into your workflow. Native ATS integrations are something we scope as part of agency-led custom builds; talk to us if that is on your roadmap.
CVs in English produce the most consistent output today. Polish, German, French, and Spanish CVs are usable but may produce mixed-language analysis. We are iterating on multilingual prompts as we measure quality.
Any LLM-based system carries the biases of its training data. Treat the score and rationale as a structured second opinion to surface things you might miss — not as ground truth. The recruiter remains accountable for the hiring decision and any equal-opportunity obligations under EU law.